,. C. G. K. C. G Sudha Rani, A Anusha, A Yamini, I.Srinivasa Rao
{"title":"保持警惕:利用物联网技术进行瞌睡检测","authors":",. C. G. K. C. G Sudha Rani, A Anusha, A Yamini, I.Srinivasa Rao","doi":"10.46501/ijmtst1002007","DOIUrl":null,"url":null,"abstract":"The \"Drowsiness Detection using IoT with Eye Blink Sensor and Buzzer\" project aims to address the critical issue of driver fatigue and drowsiness, a major cause of road accidents. Leveraging Internet of Things (IoT) technologies and a combination of eye blink sensors and a buzzer, this system provides a real-time solution for monitoring and alerting drivers when signs of drowsiness are detected. The project focuses on enhancing road safety by preventing accidents caused by driver fatigue Drowsiness detection is a critical aspect of ensuring safety, particularly in domains such as transportation where fatigue-related accidents pose significant risks. In recent years, the proliferation of Internet of Things (IoT) devices has enabled innovative approaches to drowsiness detection systems. This abstract outlines a novel framework for drowsiness detection utilizing IoT technologies. Our proposed system integrates various sensors, including facial recognition cameras, heart rate monitors, and accelerometers, into a networked IoT infrastructure. These sensors continuously monitor key physiological and behavioral indicators associated with drowsiness, such as eye movement patterns, blink frequency, heart rate variability, and head position changes.","PeriodicalId":13741,"journal":{"name":"International Journal for Modern Trends in Science and Technology","volume":"191 S528","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stay Alert: Drowsiness Detection with IoT Technology\",\"authors\":\",. C. G. K. C. G Sudha Rani, A Anusha, A Yamini, I.Srinivasa Rao\",\"doi\":\"10.46501/ijmtst1002007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The \\\"Drowsiness Detection using IoT with Eye Blink Sensor and Buzzer\\\" project aims to address the critical issue of driver fatigue and drowsiness, a major cause of road accidents. Leveraging Internet of Things (IoT) technologies and a combination of eye blink sensors and a buzzer, this system provides a real-time solution for monitoring and alerting drivers when signs of drowsiness are detected. The project focuses on enhancing road safety by preventing accidents caused by driver fatigue Drowsiness detection is a critical aspect of ensuring safety, particularly in domains such as transportation where fatigue-related accidents pose significant risks. In recent years, the proliferation of Internet of Things (IoT) devices has enabled innovative approaches to drowsiness detection systems. This abstract outlines a novel framework for drowsiness detection utilizing IoT technologies. Our proposed system integrates various sensors, including facial recognition cameras, heart rate monitors, and accelerometers, into a networked IoT infrastructure. These sensors continuously monitor key physiological and behavioral indicators associated with drowsiness, such as eye movement patterns, blink frequency, heart rate variability, and head position changes.\",\"PeriodicalId\":13741,\"journal\":{\"name\":\"International Journal for Modern Trends in Science and Technology\",\"volume\":\"191 S528\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Modern Trends in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46501/ijmtst1002007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Modern Trends in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46501/ijmtst1002007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stay Alert: Drowsiness Detection with IoT Technology
The "Drowsiness Detection using IoT with Eye Blink Sensor and Buzzer" project aims to address the critical issue of driver fatigue and drowsiness, a major cause of road accidents. Leveraging Internet of Things (IoT) technologies and a combination of eye blink sensors and a buzzer, this system provides a real-time solution for monitoring and alerting drivers when signs of drowsiness are detected. The project focuses on enhancing road safety by preventing accidents caused by driver fatigue Drowsiness detection is a critical aspect of ensuring safety, particularly in domains such as transportation where fatigue-related accidents pose significant risks. In recent years, the proliferation of Internet of Things (IoT) devices has enabled innovative approaches to drowsiness detection systems. This abstract outlines a novel framework for drowsiness detection utilizing IoT technologies. Our proposed system integrates various sensors, including facial recognition cameras, heart rate monitors, and accelerometers, into a networked IoT infrastructure. These sensors continuously monitor key physiological and behavioral indicators associated with drowsiness, such as eye movement patterns, blink frequency, heart rate variability, and head position changes.